Datasets:

---

evaleval

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entity-registry-data

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EvalEval Coalition 77

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
id: large_string
evaluation_id: large_string
result_index: int64
source_config: large_string
model_id: large_string
harness_id: large_string
benchmark_id: large_string
parent_benchmark_id: large_string
metric_id: large_string
benchmark_card_id: null
score: double
score_details: large_string
inference_platform: large_string
created_at: large_string
updated_at: large_string
-- schema metadata --
pandas: '{"index_columns": [], "column_indexes": [], "columns": [{"name":' + 1916
to
{'id': Value('large_string'), 'display_name': Value('large_string'), 'version': Value('null'), 'fork_url': Value('null'), 'metadata': Value('large_string'), 'review_status': Value('large_string'), 'created_at': Value('large_string'), 'updated_at': Value('large_string')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 478, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2815, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2352, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2377, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/parquet/parquet.py", line 220, in _generate_tables
                  yield Key(file_idx, batch_idx), self._cast_table(pa_table)
                                                  ~~~~~~~~~~~~~~~~^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/parquet/parquet.py", line 156, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              id: large_string
              evaluation_id: large_string
              result_index: int64
              source_config: large_string
              model_id: large_string
              harness_id: large_string
              benchmark_id: large_string
              parent_benchmark_id: large_string
              metric_id: large_string
              benchmark_card_id: null
              score: double
              score_details: large_string
              inference_platform: large_string
              created_at: large_string
              updated_at: large_string
              -- schema metadata --
              pandas: '{"index_columns": [], "column_indexes": [], "columns": [{"name":' + 1916
              to
              {'id': Value('large_string'), 'display_name': Value('large_string'), 'version': Value('null'), 'fork_url': Value('null'), 'metadata': Value('large_string'), 'review_status': Value('large_string'), 'created_at': Value('large_string'), 'updated_at': Value('large_string')}
              because column names don't match